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Agentic AI Engineer

Elastic· IT
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Remote$94.3k - $149.2kfull-timePosted 2mo ago

About the role

Role focused on building multi-agent ecosystems powered by large language models (LLMs), agent orchestration, and A2A integration frameworks to enable autonomous, collaborative workflows across Elastic’s enterprise environment.

Responsibilities

  • A2A Architecture & Multi-Agent Orchestration: Design, build, and deploy agent-to-agent (A2A) communication architectures and workflows that enable autonomous agents to collaborate, delegate tasks, and negotiate multi-step business processes.
  • LLM Integration & Tool Calling: Integrate advanced LLMs with enterprise APIs, using tool-calling methods and connecting with third-party SaaS applications.
  • Enterprise Grounding & RAG: Employ Retrieval-Augmented Generation techniques to connect enterprise context via search and vector storage engines for accurate inter-agent operations.
  • Scalable Infrastructure & IaC: Provision and manage cloud environments (AWS, Azure, GCP) using Terraform to support high concurrency for LLM inferences and multi-agent coordination.
  • DevOps & Lifecycle Management: Create CI/CD pipelines for automated testing, deployment, and versioning; regularly evaluate LLMs and agentic workflows.
  • A2A Security & Governance: Implement secure network fundamentals (VPCs, API gateways, encryption, IAM) for secure inter-agent communication.
  • LLM Observability & Evaluation: Monitor multi-agent interactions, manage token costs, detect model drift or agent loops, and assess model accuracy.
  • Documentation: Maintain detailed technical docs for LLM integration protocols, A2A interaction flows, and cloud deployments.

Qualifications

  • LLM & GenAI Expertise: Experience with integrating, fine-tuning, and optimizing foundation models; expertise in prompt engineering, tool calling, and structured outputs.
  • Agent-to-Agent (A2A) Protocols: Proven success building multi-agent systems, messaging pipelines, state management, and dynamic task delegation.
  • Agentic Frameworks: Hands-on work with LangGraph, LangChain, AutoGen, and tracing platforms like LangSmith.
  • Market Trends & Interoperability: Understanding of AI interoperability standards (e.g., MCP) and open multi-agent specs.
  • Programming: Advanced Python or TypeScript for backend orchestration, memory systems, and API services.
  • Enterprise Grounding & Vector Search: Knowledge of RAG patterns, vector databases, hybrid search, and context management.
  • DevOps & IaC: Experience with Terraform, Docker, and Kubernetes for scalable AI deployments.
  • Security & Network Fundamentals: Knowledge of secure cloud architectures, zero-trust design, private endpoints, OAuth/SAML/IAM for A2A.
  • LLM Observability & Evaluation: Experience with logging, tracing, metrics to monitor non-deterministic workflows, token costs, and output quality.
  • Enterprise AI Platform Knowledge: Familiarity with broader agentic workflows (e.g., Workday A2A, Salesforce Agentforce, ServiceNow AI Agents)

Skills

Required:GenAI project deliveryElastic Stack expertise (ESRE, RAG)Agentic frameworksDevOps and IaCSecurity & NetworkingObservability & monitoringProgramming

Benefits

  • Company-matched 401k with dollar-for-dollar matching up to 6%
  • Health coverage for employee and family in many locations
  • Flexible locations and schedules
  • Generous vacation days
  • Donation matching up to $2000
  • Volunteer hours (up to 40 hours per year)
  • Parental leave (minimum 16 weeks)
Last updated Oct 1, 2026. Interested? Apply on the company site.
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Power insights and outcomes with The Elastic Search AI Platform. See into your data and find answers that matter with enterprise solutions designed to help you accelerate time to insight.

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